Overview

Dataset statistics

Number of variables8
Number of observations2430
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory154.2 KiB
Average record size in memory65.0 B

Variable types

DateTime1
TimeSeries6
Boolean1

Timeseries statistics

Number of series6
Time series length2430
Starting point2010-01-04 00:00:00
Ending point2019-08-30 00:00:00
Period1 day, 10 hours and 49 minutes
2026-02-06T03:46:55.520908image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:55.738109image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Alerts

repaired? has constant value "False"Constant
adj close is highly overall correlated with close and 4 other fieldsHigh correlation
close is highly overall correlated with adj close and 4 other fieldsHigh correlation
high is highly overall correlated with adj close and 4 other fieldsHigh correlation
low is highly overall correlated with adj close and 4 other fieldsHigh correlation
open is highly overall correlated with adj close and 4 other fieldsHigh correlation
volume is highly overall correlated with adj close and 4 other fieldsHigh correlation
adj close is non stationaryNon stationary
close is non stationaryNon stationary
high is non stationaryNon stationary
low is non stationaryNon stationary
open is non stationaryNon stationary
volume is non stationaryNon stationary
adj close is seasonalSeasonal
close is seasonalSeasonal
high is seasonalSeasonal
low is seasonalSeasonal
open is seasonalSeasonal
volume is seasonalSeasonal
Date has unique valuesUnique

Reproduction

Analysis started2026-02-06 03:46:50.723136
Analysis finished2026-02-06 03:46:55.406441
Duration4.68 seconds
Software versionydata-profiling vv4.18.1
Download configurationconfig.json

Variables

Date
Date

Unique 

Distinct2430
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size38.0 KiB
Minimum2010-01-04 00:00:00
Maximum2019-08-30 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2026-02-06T03:46:55.917793image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:56.038261image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

adj close
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2056
Distinct (%)84.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.050523
Minimum26.209999
Maximum113.93
Zeros0
Zeros (%)0.0%
Memory size38.0 KiB
2026-02-06T03:46:56.181731image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum26.209999
5-th percentile42.196999
Q152.047501
median73.764999
Q393.877499
95-th percentile104.7
Maximum113.93
Range87.720001
Interquartile range (IQR)41.829998

Descriptive statistics

Standard deviation22.074933
Coefficient of variation (CV)0.30218721
Kurtosis-1.386272
Mean73.050523
Median Absolute Deviation (MAD)21.044998
Skewness-0.026642822
Sum177512.77
Variance487.30269
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.6066339276
2026-02-06T03:46:56.310468image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-06T03:46:56.666119image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps503
min3 days
max5 days
mean3 days, 3 hours and 11 minutes
std8 hours, 18 minutes and 9.91 seconds
2026-02-06T03:46:57.659357image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
44.659999856
 
0.2%
93.959999084
 
0.2%
53.900001534
 
0.2%
97.379997253
 
0.1%
50.790000923
 
0.1%
50.419998173
 
0.1%
47.639999393
 
0.1%
47.049999243
 
0.1%
67.040000923
 
0.1%
93.879997253
 
0.1%
Other values (2046)2395
98.6%
ValueCountFrequency (%)
26.209999081
< 0.1%
26.549999241
< 0.1%
27.450000761
< 0.1%
27.940000531
< 0.1%
28.459999081
< 0.1%
29.040000921
< 0.1%
29.420000081
< 0.1%
29.440000531
< 0.1%
29.530000691
< 0.1%
29.639999391
< 0.1%
ValueCountFrequency (%)
113.93000031
< 0.1%
113.51999661
< 0.1%
112.86000061
< 0.1%
112.79000091
< 0.1%
112.76000211
< 0.1%
112.29000091
< 0.1%
112.27999881
< 0.1%
112.20999911
< 0.1%
111.44999691
< 0.1%
111.05000311
< 0.1%
2026-02-06T03:46:56.432650image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

close
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2056
Distinct (%)84.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.050523
Minimum26.209999
Maximum113.93
Zeros0
Zeros (%)0.0%
Memory size38.0 KiB
2026-02-06T03:46:58.625970image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum26.209999
5-th percentile42.196999
Q152.047501
median73.764999
Q393.877499
95-th percentile104.7
Maximum113.93
Range87.720001
Interquartile range (IQR)41.829998

Descriptive statistics

Standard deviation22.074933
Coefficient of variation (CV)0.30218721
Kurtosis-1.386272
Mean73.050523
Median Absolute Deviation (MAD)21.044998
Skewness-0.026642822
Sum177512.77
Variance487.30269
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.6066339276
2026-02-06T03:46:58.755296image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-06T03:46:59.102974image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps503
min3 days
max5 days
mean3 days, 3 hours and 11 minutes
std8 hours, 18 minutes and 9.91 seconds
2026-02-06T03:47:00.072196image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
44.659999856
 
0.2%
93.959999084
 
0.2%
53.900001534
 
0.2%
97.379997253
 
0.1%
50.790000923
 
0.1%
50.419998173
 
0.1%
47.639999393
 
0.1%
47.049999243
 
0.1%
67.040000923
 
0.1%
93.879997253
 
0.1%
Other values (2046)2395
98.6%
ValueCountFrequency (%)
26.209999081
< 0.1%
26.549999241
< 0.1%
27.450000761
< 0.1%
27.940000531
< 0.1%
28.459999081
< 0.1%
29.040000921
< 0.1%
29.420000081
< 0.1%
29.440000531
< 0.1%
29.530000691
< 0.1%
29.639999391
< 0.1%
ValueCountFrequency (%)
113.93000031
< 0.1%
113.51999661
< 0.1%
112.86000061
< 0.1%
112.79000091
< 0.1%
112.76000211
< 0.1%
112.29000091
< 0.1%
112.27999881
< 0.1%
112.20999911
< 0.1%
111.44999691
< 0.1%
111.05000311
< 0.1%
2026-02-06T03:46:58.871194image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

high
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2003
Distinct (%)82.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.996556
Minimum27.48
Maximum114.83
Zeros0
Zeros (%)0.0%
Memory size38.0 KiB
2026-02-06T03:47:00.871419image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum27.48
5-th percentile43.068
Q152.860001
median74.740002
Q394.697498
95-th percentile105.585
Maximum114.83
Range87.350002
Interquartile range (IQR)41.837498

Descriptive statistics

Standard deviation22.119629
Coefficient of variation (CV)0.29892781
Kurtosis-1.397453
Mean73.996556
Median Absolute Deviation (MAD)21.170002
Skewness-0.026499358
Sum179811.63
Variance489.27797
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.6115468267
2026-02-06T03:47:00.999375image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-06T03:47:01.347092image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps503
min3 days
max5 days
mean3 days, 3 hours and 11 minutes
std8 hours, 18 minutes and 9.91 seconds
2026-02-06T03:47:02.319323image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
46.529998785
 
0.2%
97.690002444
 
0.2%
52.779998784
 
0.2%
53.430000314
 
0.2%
92.879997254
 
0.2%
48.740001684
 
0.2%
97.819999694
 
0.2%
94.639999394
 
0.2%
46.409999854
 
0.2%
86.370002754
 
0.2%
Other values (1993)2389
98.3%
ValueCountFrequency (%)
27.479999541
< 0.1%
28.579999921
< 0.1%
29.219999311
< 0.1%
29.659999851
< 0.1%
30.209999081
< 0.1%
30.251
< 0.1%
30.610000611
< 0.1%
30.729999541
< 0.1%
31.180000311
< 0.1%
31.379999161
< 0.1%
ValueCountFrequency (%)
114.83000181
< 0.1%
114.18000031
< 0.1%
113.97000121
< 0.1%
113.48000341
< 0.1%
113.45999911
< 0.1%
113.40000151
< 0.1%
113.22000121
< 0.1%
113.18000031
< 0.1%
112.63999941
< 0.1%
112.48000341
< 0.1%
2026-02-06T03:47:01.116780image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

low
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2038
Distinct (%)83.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.042424
Minimum26.049999
Maximum112.25
Zeros0
Zeros (%)0.0%
Memory size38.0 KiB
2026-02-06T03:47:03.348073image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum26.049999
5-th percentile41.4615
Q151.029999
median72.52
Q392.9275
95-th percentile103.861
Maximum112.25
Range86.200001
Interquartile range (IQR)41.897501

Descriptive statistics

Standard deviation21.942269
Coefficient of variation (CV)0.30457427
Kurtosis-1.3791629
Mean72.042424
Median Absolute Deviation (MAD)20.889999
Skewness-0.024296874
Sum175063.09
Variance481.46316
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.5830230706
2026-02-06T03:47:03.477330image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-06T03:47:03.830043image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps503
min3 days
max5 days
mean3 days, 3 hours and 11 minutes
std8 hours, 18 minutes and 9.91 seconds
2026-02-06T03:47:04.800745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
92.860000614
 
0.2%
96.260002144
 
0.2%
96.510002144
 
0.2%
90.660003663
 
0.1%
96.370002753
 
0.1%
93.080001833
 
0.1%
903
 
0.1%
97.370002753
 
0.1%
46.669998173
 
0.1%
85.110000613
 
0.1%
Other values (2028)2397
98.6%
ValueCountFrequency (%)
26.049999241
< 0.1%
26.190000531
< 0.1%
26.950000761
< 0.1%
27.239999771
< 0.1%
27.739999771
< 0.1%
27.870000841
< 0.1%
28.209999081
< 0.1%
28.700000761
< 0.1%
28.729999541
< 0.1%
29.049999241
< 0.1%
ValueCountFrequency (%)
112.251
< 0.1%
111.69000241
< 0.1%
111.12000271
< 0.1%
111.08000181
< 0.1%
1111
< 0.1%
110.81999971
< 0.1%
110.70999911
< 0.1%
110.30000311
< 0.1%
110.11000061
< 0.1%
109.11000061
< 0.1%
2026-02-06T03:47:03.597530image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

open
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2014
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.070329
Minimum27.299999
Maximum113.89
Zeros0
Zeros (%)0.0%
Memory size38.0 KiB
2026-02-06T03:47:05.520231image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum27.299999
5-th percentile42.103001
Q152.054999
median73.880001
Q393.877499
95-th percentile104.76
Maximum113.89
Range86.59
Interquartile range (IQR)41.822499

Descriptive statistics

Standard deviation22.056567
Coefficient of variation (CV)0.30185395
Kurtosis-1.3872633
Mean73.070329
Median Absolute Deviation (MAD)21.040001
Skewness-0.026705827
Sum177560.9
Variance486.49216
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.6106746874
2026-02-06T03:47:05.649512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-06T03:47:05.998913image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps503
min3 days
max5 days
mean3 days, 3 hours and 11 minutes
std8 hours, 18 minutes and 9.91 seconds
2026-02-06T03:47:06.971393image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
93.489997865
 
0.2%
99.199996955
 
0.2%
97.300003054
 
0.2%
49.310001374
 
0.2%
95.790000924
 
0.2%
66.620002754
 
0.2%
46.279998783
 
0.1%
48.790000923
 
0.1%
99.480003363
 
0.1%
61.549999243
 
0.1%
Other values (2004)2392
98.4%
ValueCountFrequency (%)
27.299999241
< 0.1%
27.340000151
< 0.1%
28.329999921
< 0.1%
28.350000381
< 0.1%
28.360000611
< 0.1%
29.079999921
< 0.1%
29.139999391
< 0.1%
29.200000761
< 0.1%
29.719999311
< 0.1%
29.751
< 0.1%
ValueCountFrequency (%)
113.88999941
< 0.1%
113.27999881
< 0.1%
113.12999731
< 0.1%
112.98000341
< 0.1%
112.81999971
< 0.1%
112.33999631
< 0.1%
112.15000151
< 0.1%
111.88999941
< 0.1%
111.37000271
< 0.1%
110.68000031
< 0.1%
2026-02-06T03:47:05.770674image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

repaired?
Boolean

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size21.4 KiB
False
2430 
ValueCountFrequency (%)
False2430
100.0%
2026-02-06T03:47:07.945625image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

volume
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2423
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean416384.85
Minimum48516
Maximum1311000
Zeros0
Zeros (%)0.0%
Memory size38.0 KiB
2026-02-06T03:47:08.049479image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum48516
5-th percentile150918.7
Q1253456.25
median351326
Q3562662.25
95-th percentile806731.6
Maximum1311000
Range1262484
Interquartile range (IQR)309206

Descriptive statistics

Standard deviation212491.76
Coefficient of variation (CV)0.51032539
Kurtosis0.06878631
Mean416384.85
Median Absolute Deviation (MAD)129585.5
Skewness0.81783706
Sum1.0118152 × 109
Variance4.5152749 × 1010
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.2377250318
2026-02-06T03:47:08.191905image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-06T03:47:08.552990image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps503
min3 days
max5 days
mean3 days, 3 hours and 11 minutes
std8 hours, 18 minutes and 9.91 seconds
2026-02-06T03:47:09.544049image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
2263432
 
0.1%
2975222
 
0.1%
3179972
 
0.1%
1324272
 
0.1%
2500382
 
0.1%
5988362
 
0.1%
8956432
 
0.1%
4810341
 
< 0.1%
4504721
 
< 0.1%
5422541
 
< 0.1%
Other values (2413)2413
99.3%
ValueCountFrequency (%)
485161
< 0.1%
518771
< 0.1%
656661
< 0.1%
837021
< 0.1%
846271
< 0.1%
908241
< 0.1%
913981
< 0.1%
927801
< 0.1%
931301
< 0.1%
952701
< 0.1%
ValueCountFrequency (%)
13110001
< 0.1%
12535661
< 0.1%
11823271
< 0.1%
11735811
< 0.1%
11473891
< 0.1%
11362321
< 0.1%
11354401
< 0.1%
11249591
< 0.1%
11080521
< 0.1%
10956431
< 0.1%
2026-02-06T03:47:08.316394image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

Interactions

2026-02-06T03:46:54.541308image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:52.431887image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:52.872837image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:53.290641image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:53.708368image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:54.124674image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:54.619819image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:52.506568image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:52.940081image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:53.360518image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:53.777715image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:54.191994image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:54.699663image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:52.575834image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:53.006723image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:53.430246image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:53.844006image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:54.259762image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:54.776123image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:52.645857image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:53.075217image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:53.496376image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:53.910223image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:54.330975image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:54.855071image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:52.715967image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:53.143609image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:53.563515image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:53.977283image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:54.397507image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:55.155696image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:52.785404image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:53.213943image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:53.631019image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:54.044951image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:46:54.463629image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2026-02-06T03:47:10.196528image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
adj closeclosehighlowopenvolume
adj close1.0001.0000.9990.9990.998-0.602
close1.0001.0000.9990.9990.998-0.602
high0.9990.9991.0000.9990.999-0.596
low0.9990.9990.9991.0000.999-0.607
open0.9980.9980.9990.9991.000-0.600
volume-0.602-0.602-0.596-0.607-0.6001.000

Missing values

2026-02-06T03:46:55.275571image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2026-02-06T03:46:55.357583image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Dateadj closeclosehighlowopenrepaired?volume
2010-01-042010-01-0481.51000281.51000281.68000079.62999779.629997False263542
2010-01-052010-01-0581.76999781.76999782.00000080.94999781.629997False258887
2010-01-062010-01-0683.18000083.18000083.51999780.84999881.430000False370059
2010-01-072010-01-0782.66000482.66000483.36000182.26000283.199997False246632
2010-01-082010-01-0882.75000082.75000083.47000181.80000382.650002False310377
2010-01-112010-01-1182.51999782.51999783.94999781.95999982.879997False296304
2010-01-122010-01-1280.79000180.79000182.33999679.91000482.070000False333866
2010-01-132010-01-1379.65000279.65000280.66999878.37000380.059998False401627
2010-01-142010-01-1479.38999979.38999980.36000178.91999879.629997False275404
2010-01-152010-01-1578.00000078.00000079.30999877.69999779.199997False200555
Dateadj closeclosehighlowopenrepaired?volume
2019-08-192019-08-1956.20999956.20999956.41000054.84000054.959999False113571
2019-08-202019-08-2056.34000056.34000056.59999855.27999956.099998False659258
2019-08-212019-08-2155.68000055.68000057.13000155.54999956.049999False704035
2019-08-222019-08-2255.34999855.34999856.45999954.84999855.939999False621573
2019-08-232019-08-2354.16999854.16999855.59999853.24000255.349998False807151
2019-08-262019-08-2653.63999953.63999955.25999852.95999953.250000False679022
2019-08-272019-08-2754.93000054.93000055.72000153.68999953.759998False596624
2019-08-282019-08-2855.77999955.77999956.75000055.34000055.709999False674048
2019-08-292019-08-2956.70999956.70999956.88999955.43000055.880001False630760
2019-08-302019-08-3055.09999855.09999856.72000154.54999956.630001False708268